1. Field
One or more exemplary embodiments relate to a magnetic resonance imaging (MRI) apparatus and method, and more particularly, to an MRI apparatus and method for obtaining 3-dimensional (3D) MR images by undersampling in a 3D K-space.
2. Description of the Related Art
A magnetic resonance imaging (MRI) apparatus is an apparatus for capturing images of objects by using magnetic fields. The MRI apparatus is widely used for accurate diagnosis of medical issues relating to human patients, because the MRI apparatus may provide 3-dimensional (3D) images of bones, discs, joints, nerves, ligaments, and other parts of the human body from a desired angle.
The MRI apparatus acquires magnetic resonance (MR) signals, reconstructs the acquired MR signals, and outputs the reconstructed MR signals as images. For example, the MRI apparatus may acquire MR signals by using a radio frequency (RF) multi-coil that includes RF coils, permanent magnets, and gradient coils.
For example, a pulse sequence for generating RF signals may be applied to an RF multi-coil, and the generated RF signals may be applied to an object. MR signals are generated correspondingly to the applied RF signals, and sampled in order to restore a MR image.
According to current MRI technology, an MRI scan time may be approximately one hour. A general MRI apparatus includes a long and narrow tube (hereinafter, referred to as ‘MRI tunnel’), and a patient who wants to be MRI scanned musts enter the MRI tunnel and stay still during the scanning procedure. Therefore, it may be difficult to perform MRI scanning on seriously ill patients or patients with claustrophobia, and even general patients may feel bored and inconvenienced due to the long scan time.
Thus, an image processing apparatus and method for reducing an MRI scan time are required.
In order to reduce the MRI scan time, instead of sampling MR signals at all points of a K-space image, i.e., full sampling, the MR signals may be acquired at some points of the K-space image and not acquired at other points of the K-space image, i.e., undersampling may be performed. In this case, signals that are not acquired from incomplete K-space data acquired by undersampling may be restored by calibration.
An example of an image processing method of restoring MR images may include Generalized Autocalibrating Partially Parallel Acquisitions (GRAPPA).
In particular, GRAPPA is an imaging technique that is based on a K-space, which includes calculating a spatial correlation coefficient by self-calibration and estimating unacquired signals by using the calculated spatial correlation coefficient. The spatial correlation coefficient is a spatial interaction value between a calibration signal and an estimated source signal nearby the calibration signal. The spatial correlation coefficient may also be referred to as a convolution kernel.
According to the GRAPPA technique, unacquired K-space lines may be restored according to channels by using estimated line data that includes undersampled data and additionally acquired autocalibration signal (ACS) line data.
When image signal data is damaged due to noise or a spatial interaction value is changed while restoring K-space data by calibration, aliasing artifacts and amplified noise may occur in a resulting MR image.
Therefore, it is necessary to provide an imaging method and apparatus for restoring an MR image with improved quality by reducing aliasing artifacts and preventing amplified noise.